{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T00:10:05Z","timestamp":1783123805621,"version":"3.54.6"},"reference-count":79,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T00:00:00Z","timestamp":1763596800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Artif. Intell."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Systematic literature reviews (SLRs) are critical to health research and decision-making but are often time- and labor-intensive. Artificial intelligence (AI) tools like large language models (LLMs) provide a promising way to automate these processes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We conducted a systematic literature review on the cost-effectiveness of adult pneumococcal vaccination and prospectively assessed the performance of our AI-assisted review platform, Intelligent Systematic Literature Review (ISLaR) 2.0, compared to expert researchers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>ISLaR demonstrated high accuracy (0.87 full-text screening; 0.86 data extraction), precision (0.88; 0.86), and sensitivity (0.91; 0.98) in article screening and data extraction tasks, but lower specificity (0.79; 0.42), especially when extracting data from tables. The platform reduced abstract and full-text screening time by over 90% compared to human reviewers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The platform has strong potential to reduce reviewer workload but requires further development.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/frai.2025.1662202","type":"journal-article","created":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T13:00:31Z","timestamp":1763643631000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Analysis of article screening and data extraction performance by an AI systematic literature review platform"],"prefix":"10.3389","volume":"8","author":[{"given":"Kelsie","family":"Cassell","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abiodun","family":"Ologunowa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Majid","family":"Rastegar-Mojarad","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bianca","family":"Chun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi-Ling","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nicole","family":"Cossrow","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,11,20]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"1939","DOI":"10.1093\/jamia\/ocae166","article-title":"A question-answering framework for automated abstract screening using large language models","volume":"31","author":"Akinseloyin","year":"2024","journal-title":"J. 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